Care of terminally ill / Palliative care

HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder

Although end-to-end autonomous driving (E2E-AD) technologies have made significant progress in recent years, there remains an unsatisfactory performance on closed-loop evaluation. The potential of leveraging planning in query design and interaction has not yet been fully explored. In this paper, we introduce a multi-granularity planning query representation that integrates heterogeneous waypoint...

MsaMIL-Net: An End-to-End Multi-Scale Aware Multiple Instance Learning Network for Efficient Whole Slide Image Classification

Bag-based Multiple Instance Learning (MIL) approaches have emerged as the mainstream methodology for Whole Slide Image (WSI) classification. However, most existing methods adopt a segmented training strategy, which first extracts features using a pre-trained feature extractor and then aggregates these features through MIL. This segmented training approach leads to insufficient collaborative opti...

Reasoning in visual navigation of end-to-end trained agents: a dynamical systems approach

Progress in Embodied AI has made it possible for end-to-end-trained agents to navigate in photo-realistic environments with high-level reasoning and...

CATPlan: Loss-based Collision Prediction in End-to-End Autonomous Driving

In recent years, there has been increased interest in the design, training, and evaluation of end-to-end autonomous driving (AD) systems. One often ...

TimeLoc: A Unified End-to-End Framework for Precise Timestamp Localization in Long Videos

Temporal localization in untrimmed videos, which aims to identify specific timestamps, is crucial for video understanding but remains challenging. T...

End-to-End Action Segmentation Transformer

Existing approaches to action segmentation use pre-computed frame features extracted by methods which have been trained on tasks that are different ...

TransParking: A Dual-Decoder Transformer Framework with Soft Localization for End-to-End Automatic Parking

In recent years, fully differentiable end-to-end autonomous driving systems have become a research hotspot in the field of intelligent transportatio...

A Map-free Deep Learning-based Framework for Gate-to-Gate Monocular Visual Navigation aboard Miniaturized Aerial Vehicles

Palm-sized autonomous nano-drones, i.e., sub-50g in weight, recently entered the drone racing scenario, where they are tasked to avoid obstacles and...

An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization

Multi-sensor fusion is essential for autonomous vehicle localization, as it is capable of integrating data from various sources for enhanced accurac...

Security and Real-time FPGA integration for Learned Image Compression

Learnable Image Compression (LIC) has proven capable of outperforming standardized video codecs in compression efficiency. However, achieving both r...

DDCSR: A Novel End-to-End Deep Learning Framework for Cortical Surface Reconstruction from Diffusion MRI

Diffusion MRI (dMRI) plays a crucial role in studying brain white matter connectivity. Cortical surface reconstruction (CSR), including the inner wh...

Generative Model-Assisted Demosaicing for Cross-multispectral Cameras

As a crucial part of the spectral filter array (SFA)-based multispectral imaging process, spectral demosaicing has exploded with the proliferation o...

Efficient End-to-end Visual Localization for Autonomous Driving with Decoupled BEV Neural Matching

Accurate localization plays an important role in high-level autonomous driving systems. Conventional map matching-based localization methods solve t...

CARIL: Confidence-Aware Regression in Imitation Learning for Autonomous Driving

End-to-end vision-based imitation learning has demonstrated promising results in autonomous driving by learning control commands directly from exper...

Foundation Models -- A Panacea for Artificial Intelligence in Pathology?

The role of artificial intelligence (AI) in pathology has evolved from aiding diagnostics to uncovering predictive morphological patterns in whole s...

VDT-Auto: End-to-end Autonomous Driving with VLM-Guided Diffusion Transformers

In autonomous driving, dynamic environment and corner cases pose significant challenges to the robustness of ego vehicle's decision-making. To addre...

Comet: Fine-grained Computation-communication Overlapping for Mixture-of-Experts

Mixture-of-experts (MoE) has been extensively employed to scale large language models to trillion-plus parameters while maintaining a fixed computat...

PhenoProfiler: Advancing Phenotypic Learning for Image-based Drug Discovery

In the field of image-based drug discovery, capturing the phenotypic response of cells to various drug treatments and perturbations is a crucial ste...

ObjectVLA: End-to-End Open-World Object Manipulation Without Demonstration

Imitation learning has proven to be highly effective in teaching robots dexterous manipulation skills. However, it typically relies on large amounts...

SpargeAttn: Accurate Sparse Attention Accelerating Any Model Inference

An efficient attention implementation is essential for large models due to its quadratic time complexity. Fortunately, attention commonly exhibits s...