Multimodal Representation Learning and Set Attention for LWIR In-Scene Atmospheric Compensation
نویسندگان
چکیده
منابع مشابه
LWIR pupil imaging & prospects for background compensation
A previous paper described LWIR Pupil Imaging with a sensitive, low-flux focal plane array, and behavior of this type of system for higher flux operations as understood at the time. We continue this investigation, and report on a more detailed characterization of the system over a broad range of pixel fluxes. This characterization is then shown to enable non-uniformity correction over the flux ...
متن کاملLatent Semantic Representation Learning for Scene Classification
The performance of machine learning methods is heavily dependent on the choice of data representation. In real world applications such as scene recognition problems, the widely used low-level input features can fail to explain the high-level semantic label concepts. In this work, we address this problem by proposing a novel patchbased latent variable model to integrate latent contextual represe...
متن کاملScene Representation for a Sparse Set of Multi-view Images
In this paper, we propose a novel scene representation for a sparse set of calibrated multi-view images of a nonLambertian scene. This representation is capable of providing realistic immersive experience. Firstly, the foreground objects are extracted from the background. Then, they are operated independently. The background of the middle views is used for representing the background of the sce...
متن کاملMultimodal sparse representation learning and applications
Unsupervised methods have proven effective for discriminative tasks in a singlemodality scenario. In this paper, we present a multimodal framework for learning sparse representations that can capture semantic correlation between modalities. The framework can model relationships at a higher level by forcing the shared sparse representation. In particular, we propose the use of joint dictionary l...
متن کاملRepresentation Models and Machine Learning Techniques for Scene Classificatio
Scene classification is a fundamental process of human vision that allows us to efficiently and rapidly analyze our surroundings. Humans are able to recognize complex visual scenes at a single glance, despite the number of objects with different poses, colors, shadows and textures that may be contained in the scenes. Understanding the robustness and rapidness of this human ability has been a fo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
سال: 2021
ISSN: 1939-1404,2151-1535
DOI: 10.1109/jstars.2020.3034421