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Found 12 papers, 6 papers with code
CertViT: Certified Robustness of Pre-Trained Vision Transformers
We show that CertViT networks have better certified accuracy than state-of-the-art Lipschitz trained networks.
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results
The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection.
GeoEngine: A Platform for Production-Ready Geospatial Research
In this paper we introduce the GeoEngine platform for reproducible and production-ready geospatial machine learning research.
Sparsifying Networks via Subdifferential Inclusion
Sparsifying deep neural networks is of paramount interest in many areas, especially when those networks have to be implemented on low-memory devices.
Modeling Electrical Motor Dynamics using Encoder-Decoder with Recurrent Skip Connection
In this paper, we explore the feasibility of modeling the dynamics of an electrical motor by following a data-driven approach, which uses only its inputs and outputs and does not make any assumption on its internal behaviour.
A Survey on Machine Learning Applied to Dynamic Physical Systems
This survey is on recent advancements in the intersection of physical modeling and machine learning.
Diversity in Fashion Recommendation using Semantic Parsing
In this paper, we propose to recommend images by explicitly learning and exploiting part based similarity.
Making Third Person Techniques Recognize First-Person Actions in Egocentric Videos
Unlike third person domain, researchers have divided first-person actions into two categories: involving hand-object interactions and the ones without, and developed separate techniques for the two action categories.
MAPEL: Multi-Agent Pursuer-Evader Learning using Situation Report
We present a detailed analysis of how these two cooperation methods perform when the number of agents in the game are increased.
Multi Label Restricted Boltzmann Machine for Non-Intrusive Load Monitoring
Some recent studies have proposed that if we frame Non-Intrusive Load Monitoring (NILM) as a multi-label classification problem, the need for appliance-level data can be avoided.
Collaborative Filtering with Label Consistent Restricted Boltzmann Machine
The possibility of employing restricted Boltzmann machine (RBM) for collaborative filtering has been known for about a decade.
Detecting Urban Changes with Recurrent Neural Networks from Multitemporal Sentinel-2 Data
\begin{abstract} The advent of multitemporal high resolution data, like the Copernicus Sentinel-2, has enhanced significantly the potential of monitoring the earth's surface and environmental dynamics.
