Accurate skin disease detection is one of the most challenging tasks due to high-class imbalance and limited labeled datasets. Recently Deep Convolutional Neural Network (DCNN) with ensemble learning has achieved sign...
详细信息
Accurate skin disease detection is one of the most challenging tasks due to high-class imbalance and limited labeled datasets. Recently Deep Convolutional Neural Network (DCNN) with ensemble learning has achieved significant popularity in skin cancer classification. However, implementing DCNN models with ensemble learning is not feasible for deployment on portable diagnostic devices due to the limitation in computing resources and computing time. This paper proposes a Channel Attention and Adaptive Class Balanced Focal Loss function based lightweight Deep CNN model (CACBL-Net) for handling the issues of data imbalance and limited computing resources of portable diagnostic devices, such as mobile phones or tablets. Channel attention explores interdependencies between channels by recalibrating channel-wise feature responses. To deal with the issue of high-class imbalance, the proposed method used an adaptive class balance focal loss function which can quickly concentrate the model on complex cases while automatically downweighting the contribution of easy examples during training. The proposed CACBL-Net is validated on three popular skin cancer datasets which are HAM-10000, PAD-UFES-20, and MED-NODE. Dermoscopic, non-dermoscopic and smartphone images are taken from all three datasets for experimental work. The quantitative findings indicate that the proposed CACBL-Net model achieved a sensitivity of 90.60%, 91.88%, and 91.31% for the HAM-10000, PAD-UFES-20, and MED-NODE datasets, respectively. Additionally, the average prediction time per patient was recorded at 0.006, 0.010, and 0.011 s. These results demonstrate superior performance compared to other state-of-the-art deep learning models. The experimental finding suggested that the proposed method can achieve a significant performance at a low cost of computational resources and inference time, which makes it potentially feasible for deployment in portable diagnostic devices for automated diagnosis of skin lesions.
This paper makes a literature survey on biometric image quality assessment (BIQA) techniques focusing on physiological traits. It covers a wide range of methodologies, metrics and evaluation techniques. Objective imag...
详细信息
The structure and dynamic nature of real-world networks can be revealed by communities that help in promotion of recommendation *** Media platforms were initially developed for effective communication,but now it is be...
详细信息
The structure and dynamic nature of real-world networks can be revealed by communities that help in promotion of recommendation *** Media platforms were initially developed for effective communication,but now it is being used widely for extending and to obtain profit among business *** numerous data generated through these platforms are utilized by many companies that make a huge profit out of it.A giant network of people in social media is grouped together based on their similar properties to form a ***-nity detection is recent topic among the research community due to the increase usage of online social *** is one of a significant property of a net-work that may have many communities which have similarity among *** detection technique play a vital role to discover similarities among the nodes and keep them strongly *** nodes in a network are grouped together in a single *** can be merged together to avoid lot of groups if there exist more edges between *** Learning algorithms use community detection to identify groups with common properties and thus for recommen-dation systems,health care assistance systems and many *** the above,this paper presents alternative method SimEdge-CD(Similarity and Edge between's based Community Detection)for community *** two stages of SimEdge-CD initiallyfind the similarity among nodes and group them into one *** the second stage,it identifies the exact affiliations of boundary nodes using edge betweenness to create well defined *** of proposed method on synthetic and real datasets proved to achieve a better accuracy-efficiency trade-of compared to other existing *** proposed SimEdge-CD achieves ideal value of 1 which is higher than existing sim closure like LPA,Attractor,Leiden and walktrap techniques.
Background: Epilepsy is a neurological disorder that leads to seizures. This occurs due to excessive electrical discharge by the brain cells. An effective seizure prediction model can aid in improving the lifestyle of...
详细信息
Introduction: Remote data exchange operations in healthcare are observed, consult-ed, monitored and treated by the Internet of Medical Things (IoMT). It is an extension of the Internet of Things (IoT). Method: At the ...
详细信息
Throughout the last decades, researchers have modelled a variety of software reliability growth models for estimating measures of reliability. In the present paper, we have classified faults into four divergent types ...
详细信息
Video forgery detection has become increasingly critical due to the rise of sophisticated video manipulation techniques. Traditional methods often struggle to keep up with the ever-evolving sophistication of forgery t...
详细信息
The emergence of the Internet-of-Things is anticipated to create a vast market for what are known as smart edge devices,opening numerous opportunities across countless domains,including personalized healthcare and adv...
详细信息
The emergence of the Internet-of-Things is anticipated to create a vast market for what are known as smart edge devices,opening numerous opportunities across countless domains,including personalized healthcare and advanced *** 3D integration,edge devices can achieve unprecedented miniaturization while simultaneously boosting processing power and minimizing energy ***,we demonstrate a back-end-of-line compatible optoelectronic synapse with a transfer learning method on health care applications,including electroencephalogram(EEG)-based seizure prediction,electromyography(EMG)-based gesture recognition,and electrocardiogram(ECG)-based arrhythmia *** experiments on three biomedical datasets,we observe the classification accuracy improvement for the pretrained model with 2.93%on EEG,4.90%on ECG,and 7.92%on EMG,*** optical programming property of the device enables an ultralow power(2.8×10^(-13) J)fine-tuning process and offers solutions for patient-specific issues in edge computing ***,the device exhibits impressive light-sensitive characteristics that enable a range of light-triggered synaptic functions,making it promising for neuromorphic vision *** display the benefits of these intricate synaptic properties,a 5×5 optoelectronic synapse array is developed,effectively simulating human visual perception and memory *** proposed flexible optoelectronic synapse holds immense potential for advancing the fields of neuromorphic physiological signal processing and artificial visual systems in wearable applications.
Background: Skin diseases are common health complications around the world. One of the most unsafe types of skin cancer is melanoma. Detection of skin cancer in the early stage can reduce the mortality rate. Manually ...
详细信息
The human lungs, crucial for supplying oxygen, are vulnerable to diseases such as lung cancer, a leading cause of mortality. Timely prediction of lung cancer is essential to enable early intervention by healthcare pro...
详细信息
暂无评论