Clustering is an essential analytical tool across a wide range of scientific fields, including biology, chemistry, astronomy, and pattern recognition. This paper introduces a novel clustering algorithm as a competitiv...
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Neural representations of handwriting persist even years after paralysis, which was previously employed to build high performance brain-computerinterfaces (BCI) for brain-to-text communication. However, handwriting w...
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Image clustering, a fundamental task in computer vision, entails grouping images into distinct categories based on their intrinsic properties and similarities. Traditional (non-deep) image clustering models often stru...
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Clustering is a fundamental tool of scientific analysis, ubiquitous in disciplines from biology and chemistry to astronomy and pattern recognition. We propose a novel clustering algorithm based on the natural idea tha...
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This work presents a battery-free wireless temperature sensing chip for long-termly monitoring the food production environment. A calibrated oscillator-based CMOS temperature sensor is proposed instead of the ADC-base...
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Reward or stress,which exists extensively,causes resilient emotional fluctuations under common ***,reward or stress is a typical trigger for manic or depressive episodes of bipolar disorder(BD),which is corroborated b...
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Reward or stress,which exists extensively,causes resilient emotional fluctuations under common ***,reward or stress is a typical trigger for manic or depressive episodes of bipolar disorder(BD),which is corroborated by psychological theory,biological findings,and psychosocial treatment approaches[1,2].During an episode of BD,the affective aberration can be persistent and switchable,accompanied by opposite constellations of cognitive and psychomotor *** by uncontrollable mood ranging in severity,duration,and polarity,to disentangle the pathophysiology mechanism of BD is to delineate the mystery of affective fluctuations driven by reward or stress.
Broad learning system (BLS) has to undergo a vectorization operation before modeling image data, which makes it challenging for BLS to learn local semantic features. Thus, various convolutional-based broad learning sy...
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Image clustering, a fundamental task in computer vision, entails grouping images into distinct categories based on their intrinsic properties and similarities. Traditional (non-deep) image clustering models often stru...
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ISBN:
(数字)9781665410205
ISBN:
(纸本)9781665410212
Image clustering, a fundamental task in computer vision, entails grouping images into distinct categories based on their intrinsic properties and similarities. Traditional (non-deep) image clustering models often struggle to achieve high accuracy due to variations in pose, illumination, or occlusion within image datasets, which frequently lead to multi-modal clusters. In recent years, deep neural networks, with their robust representation learning capabilities, have demonstrated considerable accuracy in image clustering tasks. However, the high computational costs and lack of interpretability of deep models have limited their practical application. In this paper, we introduce the MaxFeature Torque Clustering (MFTC) model, a non-deep approach designed as a transitional solution that bridges the gap between traditional and deep image clustering models. MFTC stands out for its accuracy, outperforming conventional image clustering methods, and provides greater interpretability, an aspect often lacking in deep models. Across six publicly available image datasets, the non-deep MFTC model achieved accuracy comparable to or better than previous state-of-the-art (SOTA) deep image clustering models. The codes are available 1 .
Biomedical Named Entity Recognition (NER) is a crucial task in extracting information from biomedical texts. However, the diversity of professional terminology, semantic complexity, and the widespread presence of syno...
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Respiratory signals are crucial for decoding olfactory neural circuits and understanding respiration-entrained local field potential (LFP) rhythms. Acquiring high-precision respiratory signals often requires additiona...
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