Breast cancer is the main lead of women's cancer-related mortalities. Therefore, early detection is imperative for preventing breast cancer from developing to advanced stages. Moreover, the emergence of computer-a...
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As one of the most effective methods to improve the accuracy and robustness of speech tasks,the audio-visual fusion approach has recently been introduced into the field of Keyword Spotting(KWS).However,existing audio-...
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As one of the most effective methods to improve the accuracy and robustness of speech tasks,the audio-visual fusion approach has recently been introduced into the field of Keyword Spotting(KWS).However,existing audio-visual keyword spotting models are limited to detecting isolated words,while keyword spotting for unconstrained speech is still a challenging *** this end,an Audio-Visual Keyword Transformer(AVKT)network is proposed to spot keywords in unconstrained video *** authors present a transformer classifier with learnable CLS tokens to extract distinctive keyword features from the variable-length audio and visual *** outputs of audio and visual branches are combined in a decision fusion *** humans can easily notice whether a keyword appears in a sentence or not,our AVKT network can detect whether a video clip with a spoken sentence contains a pre-specified ***,the position of the keyword is localised in the attention map without additional position ***-imental results on the LRS2-KWS dataset and our newly collected PKU-KWS dataset show that the accuracy of AVKT exceeded 99%in clean scenes and 85%in extremely noisy *** code is available at https://***/jialeren/AVKT.
The security image of medical data for transmission is considered highly important during communication issues because of the sensitive information of medical. Encryption and steganography are used to ensure that pati...
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In the rapidly evolving landscape of Industry 4.0, the transformation of manufacturing processes is driven by the seamless integration and intelligent utilization of data. The concept of semantic interoperability is c...
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Transformers have recently lead to encouraging progress in computer *** this work,we present new baselines by improving the original Pyramid Vision Transformer(PVT v1)by adding three designs:(i)a linear complexity att...
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Transformers have recently lead to encouraging progress in computer *** this work,we present new baselines by improving the original Pyramid Vision Transformer(PVT v1)by adding three designs:(i)a linear complexity attention layer,(ii)an overlapping patch embedding,and(iii)a convolutional feed-forward *** these modifications,PVT v2 reduces the computational complexity of PVT v1 to linearity and provides significant improvements on fundamental vision tasks such as classification,detection,and *** particular,PVT v2 achieves comparable or better performance than recent work such as the Swin *** hope this work will facilitate state-ofthe-art transformer research in computer *** is available at https://***/whai362/PVT.
Analysing x-ray images for detecting Covid-19 presents one cost-effective approach. To automate this task, deep learning techniques have been suggested to reduce doctors workload. However, existing datasets classify X...
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Agriculture plays an important role in the country's economic growth. The main goal of using smart solutions based on the Internet of Things (IOT), drone surveillance and others is to increase productivity and red...
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In the last few years, with the rapid growth of the Internet of Things (IoT), ontologies have been considered as the most significant solution to resolve the heterogeneity problem in smart campus. Although the number ...
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Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network *** improve the detection capability of minority-class attacks,this s...
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Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network *** improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer *** first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class *** second layer further segments the minority class attacks through Stacking ensemble *** datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the *** results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,*** also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class *** with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection *** research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.
In high-density crowd, a unique visual motion effect called stop-and-go wave occurs, which could evolve to trampling and compression incidents. However, few computational models have been reported for stop-and-go wave...
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