In contemporary times, advancements in technology have led to a renewed interest in the development of autonomous vehicles, commonly referred to as self-driving cars. These vehicles are equipped with sensors and compu...
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In recent years,with the development of blockchain,electronic bidding auction has received more and more *** at the possible problems of privacy leakage in the current electronic bidding and auction,this paper propose...
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In recent years,with the development of blockchain,electronic bidding auction has received more and more *** at the possible problems of privacy leakage in the current electronic bidding and auction,this paper proposes an electronic bidding auction system based on blockchain against malicious adversaries,which uses the secure multi-party computation to realize secure bidding auction protocol without any trusted third *** protocol proposed in this paper is an electronic bidding auction scheme based on the threshold elliptic curve *** can be implemented without any third party to complete the bidding auction for some malicious behaviors of the participants,which can solve the problem of resisting malicious adversary *** security of the protocol is proved by the real/ideal model paradigm,and the efficiency of the protocol is *** efficiency of the protocol is verified by simulating experiments,and the protocol has practical value.
The present research examines the current issues arises with the growing usage of personal vehicles in the transportation industry. This adoption is due to the technical advancements in the automobile sector. Although...
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The security of critical infrastructure systems is crucial as they provide basic amenities and services necessary for functioning of a community, also they represent important part of country's economy. An attack ...
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Existing works have shown that fine-tuned textual transformer models achieve state-of-the-art prediction performances but are also vulnerable to adversarial text perturbations. Traditional adversarial evaluation is of...
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In this paper, we introduce InternVL 1.5, an open-source multimodal large language model(MLLM) to bridge the capability gap between open-source and proprietary commercial models in multimodal understanding. We introdu...
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In this paper, we introduce InternVL 1.5, an open-source multimodal large language model(MLLM) to bridge the capability gap between open-source and proprietary commercial models in multimodal understanding. We introduce three simple improvements.(1) Strong vision encoder: we explored a continuous learning strategy for the large-scale vision foundation model — InternViT-6B, boosting its visual understanding capabilities, and making it can be transferred and reused in different LLMs.(2) Dynamic high-resolution: we divide images into tiles ranging from 1 to 40 of 448×448 pixels according to the aspect ratio and resolution of the input images, which supports up to 4K resolution input.(3) High-quality bilingual dataset: we carefully collected a high-quality bilingual dataset that covers common scenes, document images,and annotated them with English and Chinese question-answer pairs, significantly enhancing performance in optical character recognition(OCR) and Chinese-related tasks. We evaluate InternVL 1.5 through a series of benchmarks and comparative studies. Compared to both open-source and proprietary commercial models, InternVL 1.5 shows competitive performance, achieving state-of-the-art results in 8 of 18 multimodal benchmarks. Code and models are available at https://***/OpenGVLab/InternVL.
The automated classification of immune cells plays a vital role in advancing immunological research, diagnostics, and therapeutic monitoring. This paper leverages machine learning and image processing techniques to ac...
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Facial Expression Recognition (FER) aims to detect the emotional state of facial images. It is playing an increasingly important role in several application areas, including human–computer interaction (HCI), video tr...
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Early detection of Alzheimer's disease (AD) is crucial for timely intervention and slowing its progression. This research leverages neuroimaging-based machine learning to classify cognitive impairment levels using...
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This study explores the transformative potential of image classification algorithms like VGG16, ResNet, and DenseNet, for the early detection of pancreatic tumors using medical imaging. One of the main causes of cance...
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