AIMC Topic: Algorithms

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Self-Supervised Multimodal Learning: A Survey.

IEEE transactions on pattern analysis and machine intelligence
Multimodal learning, which aims to understand and analyze information from multiple modalities, has achieved substantial progress in the supervised regime in recent years. However, the heavy dependence on data paired with expensive human annotations ...

PoseScript: Linking 3D Human Poses and Natural Language.

IEEE transactions on pattern analysis and machine intelligence
Natural language plays a critical role in many computer vision applications, such as image captioning, visual question answering, and cross-modal retrieval, to provide fine-grained semantic information. Unfortunately, while human pose is key to human...

[Advances in low-dose cone-beam computed tomography image reconstruction methods based on deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Cone-beam computed tomography (CBCT) is widely used in dentistry, surgery, radiotherapy and other medical fields. However, repeated CBCT scans expose patients to additional radiation doses, increasing the risk of secondary malignant tumors. Low-dose ...

[Cross modal translation of magnetic resonance imaging and computed tomography images based on diffusion generative adversarial networks].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
To address the issues of difficulty in preserving anatomical structures, low realism of generated images, and loss of high-frequency image information in medical image cross-modal translation, this paper proposes a medical image cross-modal translati...

[Application of multi-scale spatiotemporal networks in physiological signal and facial action unit measurement].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Multi-task learning (MTL) has demonstrated significant advantages in the field of physiological signal measurement. This approach enhances the model's generalization ability by sharing parameters and features between similar tasks, even in data-scarc...

[The analysis of invention patents in the field of artificial intelligent medical devices].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The emergence of new-generation artificial intelligence technology has brought numerous innovations to the healthcare field, including telemedicine and intelligent care. However, the artificial intelligent medical device sector still faces significan...

[Study on speech imagery electroencephalography decoding of Chinese words based on the CAM-Net model].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Speech imagery is an emerging brain-computer interface (BCI) paradigm with potential to provide effective communication for individuals with speech impairments. This study designed a Chinese speech imagery paradigm using three clinically relevant wor...

Humans program artificial delegates to accurately solve collective-risk dilemmas but lack precision.

Proceedings of the National Academy of Sciences of the United States of America
In an era increasingly influenced by autonomous machines, it is only a matter of time before strategic individual decisions that impact collective goods will also be made virtually through the use of artificial delegates. Through a series of behavior...

Automated atomic force microscopy analysis using convolutional and recurrent neural networks.

Biophysical journal
Atomic force microscope (AFM) indentation allows high-resolution spatial characterization of biomechanical properties of cells and tissues. Rapid, reproducible, and quantitative analysis of AFM force curves has been challenging due to several technic...

DTBA-net: Drug-Target Binding Affinity prediction using feature selection in hybrid CNN model.

Journal of computer-aided molecular design
In drug discovery, virtual screening and repositioning rely on accurate Drug-Target Binding Affinity (DTBA) prediction to develop effective therapies. However, DTBA prediction remains challenging due to limited annotated datasets, high-dimensional bi...