Identification of the malignancy of tissues from Histopathological images has always been an issu... more Identification of the malignancy of tissues from Histopathological images has always been an issue of concern to doctors and radiologists. This task is time-consuming, tedious and moreover very challenging. Success in finding malignancy from Histopathological images primarily depends on long-term experience, though sometimes experts disagree on their decisions. However, Computer Aided Diagnosis (CAD) techniques help the radiologist to give a second opinion that can increase the reliability of the radiologist's decision. Among the different image analysis techniques, classification of the images has always been a challenging task. Due to the intense complexity of biomedical images, it is always very challenging to provide a reliable decision about an image. The state-of-the-art Convolutional Neural Network (CNN) technique has had great success in natural image classification. Utilizing advanced engineering techniques along with the CNN, in this paper, we have classified a set of Histopathological Breast-Cancer (BC) images utilizing a state-of-the-art CNN model containing a residual block. Conventional CNN operation takes raw images as input and extracts the global features; however, the object oriented local features also contain significant information—for example, the Local Binary Pattern (LBP) represents the effective textural information, Histogram represent the pixel strength distribution, Contourlet Transform (CT) gives much detailed information about the smoothness about the edges, and Discrete Fourier Transform (DFT) derives frequency-domain information from the image. Utilizing these advantages, along with our proposed novel CNN model, we have examined the performance of the novel CNN model as Histopathological image classifier. To do so, we have introduced five cases: (a) Convolutional Neural Network Raw Image (CNN-I); (b) Convolutional Neural Network CT Histogram (CNN-CH); (c) Convolutional Neural Network CT LBP (CNN-CL); (d) Convolutional Neural Network Discrete Fourier Transform (CNN-DF); (e) Convolutional Neural Network Discrete Cosine Transform (CNN-DC). We have performed our experiments on the BreakHis image dataset. The best performance is achieved when we utilize the CNN-CH model on a 200× dataset that provides Accuracy, Sensitivity, False Positive Rate, False Negative Rate, Recall Value, Precision and F-measure of 92.19%, 94.94%, 5.07%, 1.70%, 98.20%, 98.00% and 98.00%, respectively.
Breast cancer is one of the largest causes of women's death in the world today. Advance engineeri... more Breast cancer is one of the largest causes of women's death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors' and physicians' time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN) method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN), Logic Based classifiers such as the Random Forest (RF) algorithm, Support Vector Machines (SVM), Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.
Breast Cancer is a serious threat and one of the largest causes of death of women throughout the ... more Breast Cancer is a serious threat and one of the largest causes of death of women throughout the world. The identification of cancer largely depends on digital biomedical photography analysis such as histopathological images by doctors and physicians. Analyzing histopathological images is a nontrivial task, and decisions from investigation of these kinds of images always require specialised knowledge. However, Computer Aided Diagnosis (CAD) techniques can help the doctor make more reliable decisions. The state-of-the-art Deep Neural Network (DNN) has been recently introduced for biomedical image analysis. Normally each image contains structural and statistical information. This paper classifies a set of biomedical breast cancer images (BreakHis dataset) using novel DNN techniques guided by structural and statistical information derived from the images. Specifically a Convolutional Neural Network (CNN), a Long-Short-Term-Memory (LSTM), and a combination of CNN and LSTM are proposed for breast cancer image classification. Softmax and Support Vector Machine (SVM) layers have been used for the decision-making stage after extracting features utilising the proposed novel DNN models. In this experiment the best Accuracy value of 91.00% is achieved on the 200x dataset, the best Precision value 96.00% is achieved on the 40x dataset, and the best F-Measure value is achieved on both the 40x and 100x datasets.
A vacuum cleaner robot, generally called a
robovac, is an autonomous robot that is controlled by ... more A vacuum cleaner robot, generally called a robovac, is an autonomous robot that is controlled by intelligent program. Autonomous vacuum cleaning robot will perform task like sweeping and vacuuming in a single pass. The DVR-1 vacuum cleaning robot consists of two DC motor operated wheels that allow 360 degree rotation, a castor wheel, side spinning brushes, a front bumper and a miniature vacuum pump. Sensors in the bumper are used for generating binary information of obstacle detection then they are processed by some controlling algorithms. These algorithms are used for path planning and navigation. The robot's bumper prevents them from bumping into walls and furniture by reversing or changing path accordingly.
In this paper, we improve the outage performance of a 2 by 2 Virtual MIMO system based on Compute... more In this paper, we improve the outage performance of a 2 by 2 Virtual MIMO system based on Compute-and-Forward method . The current scheme requires negotiations between the relays and destination to determine which decoded message the relay should transmit. We propose a scheme which requires no cooperation between relay and Central Office, thus reducing the transmission overhead and latency. We show that in many cases our schemes achieve the same performance as the case where decision is made globally.
This paper introduces the multiple source Multiple Destination Robot (MDR-l) having the ability t... more This paper introduces the multiple source Multiple Destination Robot (MDR-l) having the ability to choose a desired line among multiple lines autonomously. Every line has different colors as their identities. The robot can differentiate among various colors and choose a desired one to find its target.
The line follower is an autonomous robot that detects and follows a line. The path may be visible... more The line follower is an autonomous robot that detects and follows a line. The path may be visible like a black line on a white surface or may be reverse of that or it can be invisible like a magnetic field. A close loop control system is used in the robot. The robot must sense a line and maneuvers accordingly to stay on course while correcting the wrong moves using feedback mechanism thus forming a simple but yet effective closed loop System [I]. The robot is designed to follow very tight curves as the data from the sensors are continuous in nature. This robot is simple but effective having straightforward design to perform line following task.
The line follower is an autonomous robot that detects and follows a line. The path may be visible... more The line follower is an autonomous robot that detects and follows a line. The path may be visible like a black line on a white surface or may be reverse of that or it can be invisible like a magnetic field. A close loop control system is used in the robot. The robot must sense a line and maneuvers accordingly to stay on course while correcting the wrong moves using feedback mechanism thus forming a simple but yet effective closed loop System [I]. The robot is designed to follow very tight curves as the data from the sensors are continuous in nature. This robot is simple but effective having straightforward design to perform line following task.
This paper introduces a vision based object tracking robot which is driven by wheels and controll... more This paper introduces a vision based object tracking robot which is driven by wheels and controlled by a computer along with software. The objective of this project is to design a robot which is automatically controlled by computer to track and follow a colored object. Emphasis is given on precision vision based robotic applications. Image acquisition by the robot is achieved by using a PC-based webcam, then it is send to image processing software for further processing. The overall paper describes a visual sensor system used in the field of robotics for identification and tracking of the object.
To cope with the increasing demand of wireless communication services multi-carrier systems are b... more To cope with the increasing demand of wireless communication services multi-carrier systems are being used. Radio resources are very limited and efficient usages of these resources are inevitable to get optimum performance of the system. Paging channel is a low-bandwidth channel and one of the most important channels on which system performance depends significantly. Therefore it is vulnerable to even moderate overloads. In this paper, an efficient paging algorithm, Concurrent Search, is proposed for efficient use of paging channel in Multi- carrier CDMA system instead of existing sequential searching algorithm. It is shown by the simulation that the paging performance in proposed algorithm is far better than the existing system.
In this paper, we describe an effective framework for adapting electronic commerce or e-commerce ... more In this paper, we describe an effective framework for adapting electronic commerce or e-commerce services in developing countries like Bangladesh. The internet has opened up a new horizon for commerce, namely electronic commerce (e-commerce). It entails the use of the internet in the marketing, identification, payment and delivery of goods and services. At present internet facilities are available in Bangladesh. Slowly, but steadily these facilities are holding a strong position in every aspects of our life. E-commerce is one of those sectors which need more attention if we want to be a part of global business. Bangladesh is far-far away to adapt the main stream of e-commerce application. Though government is shouting to take the challenges of e-commerce, but they do not take the right step, that is why e-commerce dose not make any real contribution in our socio-economic life. Here we propose a model which may develop the e-commerce infrastructure of Bangladesh.
Channel properties influence the development of wireless communication systems. Unlike wired chan... more Channel properties influence the development of wireless communication systems. Unlike wired channels that are stationary and predictable, radio channels are extremely random and dont offer easy analysis. A Radio Propagation Model (RPM), also known as the Radio Wave Propagation Model (RWPM), is an empirical mathematical formulation for the characterization of radio wave propagation as a function of frequency. In mobile radio systems, path loss models are necessary for proper planning, interference estimations, frequency assignments and cell parameters which are the basic for network planning process as well as Location Based Services (LBS) techniques. Propagation models that predict the mean signal strength for an arbitrary transmitter receiver (T R) separation distance which is useful in estimating the radio coverage area of a transmitter are called large scale propagation models, since they characterize signal strength over large TR separation distances. In this paper, the large scale propagation performance of Okumura, Hata, and Lee models has been compared varying Mobile Station (MS) antenna height, Transmitter Receiver (TR) distance and Base Station (BS) antenna height, considering the system to operate at 900 MHz. Through the MATLAB simulation it is turned out that the Okumura model shows the better performance than that of the other large scale propagation models.
Identification of the malignancy of tissues from Histopathological images has always been an issu... more Identification of the malignancy of tissues from Histopathological images has always been an issue of concern to doctors and radiologists. This task is time-consuming, tedious and moreover very challenging. Success in finding malignancy from Histopathological images primarily depends on long-term experience, though sometimes experts disagree on their decisions. However, Computer Aided Diagnosis (CAD) techniques help the radiologist to give a second opinion that can increase the reliability of the radiologist's decision. Among the different image analysis techniques, classification of the images has always been a challenging task. Due to the intense complexity of biomedical images, it is always very challenging to provide a reliable decision about an image. The state-of-the-art Convolutional Neural Network (CNN) technique has had great success in natural image classification. Utilizing advanced engineering techniques along with the CNN, in this paper, we have classified a set of Histopathological Breast-Cancer (BC) images utilizing a state-of-the-art CNN model containing a residual block. Conventional CNN operation takes raw images as input and extracts the global features; however, the object oriented local features also contain significant information—for example, the Local Binary Pattern (LBP) represents the effective textural information, Histogram represent the pixel strength distribution, Contourlet Transform (CT) gives much detailed information about the smoothness about the edges, and Discrete Fourier Transform (DFT) derives frequency-domain information from the image. Utilizing these advantages, along with our proposed novel CNN model, we have examined the performance of the novel CNN model as Histopathological image classifier. To do so, we have introduced five cases: (a) Convolutional Neural Network Raw Image (CNN-I); (b) Convolutional Neural Network CT Histogram (CNN-CH); (c) Convolutional Neural Network CT LBP (CNN-CL); (d) Convolutional Neural Network Discrete Fourier Transform (CNN-DF); (e) Convolutional Neural Network Discrete Cosine Transform (CNN-DC). We have performed our experiments on the BreakHis image dataset. The best performance is achieved when we utilize the CNN-CH model on a 200× dataset that provides Accuracy, Sensitivity, False Positive Rate, False Negative Rate, Recall Value, Precision and F-measure of 92.19%, 94.94%, 5.07%, 1.70%, 98.20%, 98.00% and 98.00%, respectively.
Breast cancer is one of the largest causes of women's death in the world today. Advance engineeri... more Breast cancer is one of the largest causes of women's death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors' and physicians' time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN) method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN), Logic Based classifiers such as the Random Forest (RF) algorithm, Support Vector Machines (SVM), Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.
Breast Cancer is a serious threat and one of the largest causes of death of women throughout the ... more Breast Cancer is a serious threat and one of the largest causes of death of women throughout the world. The identification of cancer largely depends on digital biomedical photography analysis such as histopathological images by doctors and physicians. Analyzing histopathological images is a nontrivial task, and decisions from investigation of these kinds of images always require specialised knowledge. However, Computer Aided Diagnosis (CAD) techniques can help the doctor make more reliable decisions. The state-of-the-art Deep Neural Network (DNN) has been recently introduced for biomedical image analysis. Normally each image contains structural and statistical information. This paper classifies a set of biomedical breast cancer images (BreakHis dataset) using novel DNN techniques guided by structural and statistical information derived from the images. Specifically a Convolutional Neural Network (CNN), a Long-Short-Term-Memory (LSTM), and a combination of CNN and LSTM are proposed for breast cancer image classification. Softmax and Support Vector Machine (SVM) layers have been used for the decision-making stage after extracting features utilising the proposed novel DNN models. In this experiment the best Accuracy value of 91.00% is achieved on the 200x dataset, the best Precision value 96.00% is achieved on the 40x dataset, and the best F-Measure value is achieved on both the 40x and 100x datasets.
A vacuum cleaner robot, generally called a
robovac, is an autonomous robot that is controlled by ... more A vacuum cleaner robot, generally called a robovac, is an autonomous robot that is controlled by intelligent program. Autonomous vacuum cleaning robot will perform task like sweeping and vacuuming in a single pass. The DVR-1 vacuum cleaning robot consists of two DC motor operated wheels that allow 360 degree rotation, a castor wheel, side spinning brushes, a front bumper and a miniature vacuum pump. Sensors in the bumper are used for generating binary information of obstacle detection then they are processed by some controlling algorithms. These algorithms are used for path planning and navigation. The robot's bumper prevents them from bumping into walls and furniture by reversing or changing path accordingly.
In this paper, we improve the outage performance of a 2 by 2 Virtual MIMO system based on Compute... more In this paper, we improve the outage performance of a 2 by 2 Virtual MIMO system based on Compute-and-Forward method . The current scheme requires negotiations between the relays and destination to determine which decoded message the relay should transmit. We propose a scheme which requires no cooperation between relay and Central Office, thus reducing the transmission overhead and latency. We show that in many cases our schemes achieve the same performance as the case where decision is made globally.
This paper introduces the multiple source Multiple Destination Robot (MDR-l) having the ability t... more This paper introduces the multiple source Multiple Destination Robot (MDR-l) having the ability to choose a desired line among multiple lines autonomously. Every line has different colors as their identities. The robot can differentiate among various colors and choose a desired one to find its target.
The line follower is an autonomous robot that detects and follows a line. The path may be visible... more The line follower is an autonomous robot that detects and follows a line. The path may be visible like a black line on a white surface or may be reverse of that or it can be invisible like a magnetic field. A close loop control system is used in the robot. The robot must sense a line and maneuvers accordingly to stay on course while correcting the wrong moves using feedback mechanism thus forming a simple but yet effective closed loop System [I]. The robot is designed to follow very tight curves as the data from the sensors are continuous in nature. This robot is simple but effective having straightforward design to perform line following task.
The line follower is an autonomous robot that detects and follows a line. The path may be visible... more The line follower is an autonomous robot that detects and follows a line. The path may be visible like a black line on a white surface or may be reverse of that or it can be invisible like a magnetic field. A close loop control system is used in the robot. The robot must sense a line and maneuvers accordingly to stay on course while correcting the wrong moves using feedback mechanism thus forming a simple but yet effective closed loop System [I]. The robot is designed to follow very tight curves as the data from the sensors are continuous in nature. This robot is simple but effective having straightforward design to perform line following task.
This paper introduces a vision based object tracking robot which is driven by wheels and controll... more This paper introduces a vision based object tracking robot which is driven by wheels and controlled by a computer along with software. The objective of this project is to design a robot which is automatically controlled by computer to track and follow a colored object. Emphasis is given on precision vision based robotic applications. Image acquisition by the robot is achieved by using a PC-based webcam, then it is send to image processing software for further processing. The overall paper describes a visual sensor system used in the field of robotics for identification and tracking of the object.
To cope with the increasing demand of wireless communication services multi-carrier systems are b... more To cope with the increasing demand of wireless communication services multi-carrier systems are being used. Radio resources are very limited and efficient usages of these resources are inevitable to get optimum performance of the system. Paging channel is a low-bandwidth channel and one of the most important channels on which system performance depends significantly. Therefore it is vulnerable to even moderate overloads. In this paper, an efficient paging algorithm, Concurrent Search, is proposed for efficient use of paging channel in Multi- carrier CDMA system instead of existing sequential searching algorithm. It is shown by the simulation that the paging performance in proposed algorithm is far better than the existing system.
In this paper, we describe an effective framework for adapting electronic commerce or e-commerce ... more In this paper, we describe an effective framework for adapting electronic commerce or e-commerce services in developing countries like Bangladesh. The internet has opened up a new horizon for commerce, namely electronic commerce (e-commerce). It entails the use of the internet in the marketing, identification, payment and delivery of goods and services. At present internet facilities are available in Bangladesh. Slowly, but steadily these facilities are holding a strong position in every aspects of our life. E-commerce is one of those sectors which need more attention if we want to be a part of global business. Bangladesh is far-far away to adapt the main stream of e-commerce application. Though government is shouting to take the challenges of e-commerce, but they do not take the right step, that is why e-commerce dose not make any real contribution in our socio-economic life. Here we propose a model which may develop the e-commerce infrastructure of Bangladesh.
Channel properties influence the development of wireless communication systems. Unlike wired chan... more Channel properties influence the development of wireless communication systems. Unlike wired channels that are stationary and predictable, radio channels are extremely random and dont offer easy analysis. A Radio Propagation Model (RPM), also known as the Radio Wave Propagation Model (RWPM), is an empirical mathematical formulation for the characterization of radio wave propagation as a function of frequency. In mobile radio systems, path loss models are necessary for proper planning, interference estimations, frequency assignments and cell parameters which are the basic for network planning process as well as Location Based Services (LBS) techniques. Propagation models that predict the mean signal strength for an arbitrary transmitter receiver (T R) separation distance which is useful in estimating the radio coverage area of a transmitter are called large scale propagation models, since they characterize signal strength over large TR separation distances. In this paper, the large scale propagation performance of Okumura, Hata, and Lee models has been compared varying Mobile Station (MS) antenna height, Transmitter Receiver (TR) distance and Base Station (BS) antenna height, considering the system to operate at 900 MHz. Through the MATLAB simulation it is turned out that the Okumura model shows the better performance than that of the other large scale propagation models.
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Papers by Abdullah Nahid
robovac, is an autonomous robot that is controlled by intelligent
program. Autonomous vacuum cleaning robot will perform task
like sweeping and vacuuming in a single pass. The DVR-1
vacuum cleaning robot consists of two DC motor operated wheels
that allow 360 degree rotation, a castor wheel, side spinning
brushes, a front bumper and a miniature vacuum pump. Sensors
in the bumper are used for generating binary information of
obstacle detection then they are processed by some controlling
algorithms. These algorithms are used for path planning and
navigation. The robot's bumper prevents them from bumping
into walls and furniture by reversing or changing path
accordingly.
robovac, is an autonomous robot that is controlled by intelligent
program. Autonomous vacuum cleaning robot will perform task
like sweeping and vacuuming in a single pass. The DVR-1
vacuum cleaning robot consists of two DC motor operated wheels
that allow 360 degree rotation, a castor wheel, side spinning
brushes, a front bumper and a miniature vacuum pump. Sensors
in the bumper are used for generating binary information of
obstacle detection then they are processed by some controlling
algorithms. These algorithms are used for path planning and
navigation. The robot's bumper prevents them from bumping
into walls and furniture by reversing or changing path
accordingly.