AIMC Topic: Humans

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Cellpose 2.0: how to train your own model.

Nature methods
Pretrained neural network models for biological segmentation can provide good out-of-the-box results for many image types. However, such models do not allow users to adapt the segmentation style to their specific needs and can perform suboptimally fo...

Structured Multimodal Attentions for TextVQA.

IEEE transactions on pattern analysis and machine intelligence
Text based Visual Question Answering (TextVQA) is a recently raised challenge requiring models to read text in images and answer natural language questions by jointly reasoning over the question, textual information and visual content. Introduction o...

Pharmacological, Non-Pharmacological Policies and Mutation: An Artificial Intelligence Based Multi-Dimensional Policy Making Algorithm for Controlling the Casualties of the Pandemic Diseases.

IEEE transactions on pattern analysis and machine intelligence
Fighting against the pandemic diseases with unique characters requires new sophisticated approaches like the artificial intelligence. This paper develops an artificial intelligence algorithm to produce multi-dimensional policies for controlling and m...

MODENN: A Shallow Broad Neural Network Model Based on Multi-Order Descartes Expansion.

IEEE transactions on pattern analysis and machine intelligence
Deep neural networks have achieved great success in almost every field of artificial intelligence. However, several weaknesses keep bothering researchers due to its hierarchical structure, particularly when large-scale parallelism, faster learning, b...

Self-Supervised Human Detection and Segmentation via Background Inpainting.

IEEE transactions on pattern analysis and machine intelligence
While supervised object detection and segmentation methods achieve impressive accuracy, they generalize poorly to images whose appearance significantly differs from the data they have been trained on. To address this when annotating data is prohibiti...

Microfluidics guided by deep learning for cancer immunotherapy screening.

Proceedings of the National Academy of Sciences of the United States of America
Immunocyte infiltration and cytotoxicity play critical roles in both inflammation and immunotherapy. However, current cancer immunotherapy screening methods overlook the capacity of the T cells to penetrate the tumor stroma, thereby significantly lim...

Piton: Investigating the Controllability of a Wearable Telexistence Robot.

Sensors (Basel, Switzerland)
The COVID-19 pandemic impacted collaborative activities, travel, and physical contact, increasing the demand for real-time interactions with remote environments. However, the existing remote communication solutions provide limited interactions and do...

A Fissure-Aided Registration Approach for Automatic Pulmonary Lobe Segmentation Using Deep Learning.

Sensors (Basel, Switzerland)
The segmentation of pulmonary lobes is important in clinical assessment, lesion location, and surgical planning. Automatic lobe segmentation is challenging, mainly due to the incomplete fissures or the morphological variation resulting from lung dise...

Deep learning in CT image segmentation of cervical cancer: a systematic review and meta-analysis.

Radiation oncology (London, England)
BACKGROUND: This paper attempts to conduct a systematic review and meta-analysis of deep learning (DLs) models for cervical cancer CT image segmentation.

A propensity score matching study on robot-assisted radical cystectomy for older patients: comparison of intracorporeal ileal conduit and cutaneous ureterostomy.

BMC urology
BACKGROUND: Robot-assisted radical cystectomy (RARC) and intracorporeal urinary diversion are less invasive than conventional procedures. However, for older patients, cutaneous ureterostomy (CUS) may be preferred because urinary diversion using the i...