Electroencephalography (EEG)-based emotion recognition is a potential research direction in the field of brain-computer interfaces (BCIs). However, its deployment on wearable devices still suffers from the challenges ...
详细信息
One of the most fundamental uses of machinelearning is the identification of handwritten digits. there has been a lot of compelling research in this field. Since everyone has different handwriting, it becomes very im...
详细信息
In this paper, the Recurrent Neural Network (RNN) model is introduced into the identification of radar emitters, which verifies the feasibility of RNN application to radar emitter identification, and the design proces...
详细信息
Withthe rapid development of Internet finance, the problem of financial fraud has become increasingly prominent, which has brought severe challenges to the security and stability of the financial industry. this paper...
详细信息
the obstacle detection industry has been developing rapidly in recent years. Obstacle detection technology has grown by leaps and bounds. Few-shot obstacle detection has a profound significance, which can help us to s...
详细信息
Malicious domains pose a significant threat to internet security, with cyber-criminals exploiting the Domain Name System (DNS) to deceive users and host malicious content. the DNS services are very significant, and he...
详细信息
ISBN:
(纸本)9783031821523;9783031821530
Malicious domains pose a significant threat to internet security, with cyber-criminals exploiting the Domain Name System (DNS) to deceive users and host malicious content. the DNS services are very significant, and hence, the DNS traffic cannot be blocked. this situation is exploited by establishing a covert tunnel for communicating commands by the malicious server, thereby taking over the control of the compromised machine. Traditional methods of detecting malicious domains, such as blacklisting, have limitations in detecting newly generated domains. In this paper, we suggest a DNS intrusion detection system using ensemble learning, where we also use the Local Interpretable Model-agnostic Explanations (LIME) to further understand the predictions of the model. For evaluating the model, the CIC-Bell-DNS2021 dataset was used. To validate the generalizability of the model, we also check it on the UNSW-NB15 dataset. the Experiments show that the proposed method outperforms the state-of-the-art results on two datasets, CIC-Bell-DNS2021 and UNSW-NB15.
Diabetic Retinopathy (DR) is an eye disease associated with chronic diabetes. It remains the primary cause of visual impairment and blindness among the global working-age population. Early detection of DR is crucial f...
详细信息
ISBN:
(纸本)9783031821554;9783031821561
Diabetic Retinopathy (DR) is an eye disease associated with chronic diabetes. It remains the primary cause of visual impairment and blindness among the global working-age population. Early detection of DR is crucial for ensuring timely diagnosis and effective treatment. this paper proposes a new homogeneous ensemble-based approach constructed using a set of hybrid architectures as base learners and two combination rules (weighted and hard voting) for referable DR detection, using fundus images from the Messidor-2, Kaggle DR, and APTOS datasets. the hybrid architectures are created using deep feature extraction techniques, dimensionality reduction techniques to reduce the size of the extracted features, and a decision tree algorithm (DT) for classification. the results showed the potential of the proposed new approach which achieved high accuracy values over the three datasets: 90.65%, 93.01%, and 83.32% using the APTOS, Kaggle DR, and Messidor-2 datasets respectively. therefore, we recommend using the proposed approach since it is impactful for referable DR classification, and it represents a promising tool to assist ophthalmologists in diagnosing DR.
Traffic patternrecognition belongs to a branch of scene recognition and has become a hot research field. Correctly identifying the transportation mode used by users to travel plays a vital role in promoting the devel...
详细信息
Since gender recognition contains a wealth of information about the differences between male and female characteristics, it is crucial and essential for many applications in commercial domains, such as human-computer ...
详细信息
the Research & Development (R&D) phase of drug development Drug discovery and development (D&D) is a complex and costly endeavor, typically requiring six to nine years [1] and four hundred to fourteen hund...
详细信息
暂无评论