9 citations · 11 across the 8 of their papers we have counts for
8 papers
Squeeze-Release: Iterative Pruning with Exact Structural Minimization
Roman Denkin, Ida Akerholm, Prashant Singh +1
Unstructured pruning produces sparse weight tensors, but the standard implementation keeps tensor shapes unchanged so the deployed model is no smaller than before pruning. We prese…
Rank-Variance Scores for Importance Sampling and Data Pruning under Label Contamination
Csongor Horváth, Ida-Maria Sintorn, Prashant Singh
Variance-optimal importance sampling and magnitude-based pruning prioritize high-loss or large-gradient examples, which under label contamination are often the corrupted ones. Unde…
PARIC: Probabilistic Attention Regularization for Language Guided Image Classification from Pre-trained Vison Language Models
Mayank Nautiyal, Stela Arranz Gheorghe, Kristiana Stefa +3
Language-guided attention frameworks have significantly enhanced both interpretability and performance in image classification; however, the reliance on deterministic embeddings fr…
Efficient High-Resolution Template Matching with Vector Quantized Nearest Neighbour Fields
Ankit Gupta, Ida-Maria Sintorn
Template matching is a fundamental problem in computer vision with applications in fields including object detection, image registration, and object tracking. Current methods rely…
Roadmap on Deep Learning for Microscopy
Giovanni Volpe, Carolina Wählby, Lei Tian +72
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasin…
Interpreting deep learning output for out-of-distribution detection
Damian Matuszewski, Ida-Maria Sintorn
Commonly used AI networks are very self-confident in their predictions, even when the evidence for a certain decision is dubious. The investigation of a deep learning model output…
Towards Better Guided Attention and Human Knowledge Insertion in Deep Convolutional Neural Networks
Ankit Gupta, Ida-Maria Sintorn
Attention Branch Networks (ABNs) have been shown to simultaneously provide visual explanation and improve the performance of deep convolutional neural networks (CNNs). In this work…
Resource- and Message Size-Aware Scheduling of Stream Processing at the Edge with application to Realtime Microscopy
Ben Blamey, Ida-Maria Sintorn, Andreas Hellander +1
Whilst computational resources at the cloud edge can be leveraged to improve latency and reduce the costs of cloud services for a wide variety mobile, web, and IoT applications; su…