Publication

ADDRESSING ANNOTATION IMPRECISION FOR TREE CROWN DELINEATION USING THE RANDCROWNS INDEX

Abstract: Supervised methods for object delineation in remote sensing require labeled ground-truth data. Gathering sufficient high quality ground-truth data is difficult, especially when the targets are of irregular shape or difficult to distinguish from the background or neighboring objects. Tree… Read More

CLASSIFICATION WITH MULTI-IMPRECISE LABELS

Abstract: Links: Citation: S. Zou, “Classification with Multi-Imprecise Labels,” Ph.D. Thesis, Gainesville, FL, 2021. @phdthesis{Zou2021Thesis, author = {Sheng Zou}, title = {Classification with Multi-Imprecise Labels}, school = {Univ. of Florida}, year = {2021}, address = {Gainesville, FL}, month = {April},… Read More

NON-INVASIVE HEART RATE ESTIMATION FROM BALLISTOCARDIOGRAMS USING BIDIRECTIONAL LSTM REGRESSION

Abstract: Non-invasive heart rate estimation is of great importance in daily monitoring of cardiovascular diseases. In this paper, a bidirectional long short term memory (bi-LSTM) regression network is developed for non-invasive heart rate estimation from the ballistocardiograms (BCG) signals. The… Read More

WALKER PRESENTS AT UF 2021 UNDERGRADUATE RESEARCH SYMPOSIUM!

Congratulations to our labmate, Sarah Walker! Sarah presented her work, titled “Divergence Regulated Encoder Network for Joint Dimensionality Reduction and Classification” at UF’s 2021 Undergraduate Research Virtual Symposium.  The virtual symposium featured outstanding undergraduate researchers across all colleges at UF.… Read More

DIVERGENCE REGULATED ENCODER NETWORK FOR JOINT DIMENSIONALITY REDUCTION AND CLASSIFICATION

Abstract: In this paper, we investigate performing joint dimensionality reduction and classification using a novel histogram neural network. Motivated by a popular dimensionality reduction approach, t-Distributed Stochastic Neighbor Embedding (t-SNE), our proposed method incorporates a classification loss computed on samples… Read More

EXPLAINABLE SYSTEMATIC ANALYSIS FOR SYNTHETIC APERTURE SONAR IMAGERY

Abstract: In this work, we present an in-depth and systematic analysis using tools such as local interpretable model-agnostic explanations (LIME) and divergence measures to analyze what changes lead to improvement in performance in fine tuned models for synthetic aperture sonar… Read More

THE WEAKLY-LABELED RAND INDEX

Abstract: Synthetic Aperture Sonar (SAS) surveys produce imagery with large regions of transition between seabed types. Due to these regions, it is difficult to label and segment the imagery and, furthermore, challenging to score the image segmentations appropriately. While there… Read More

A REMOTE SENSING DERIVED DATA SET OF 100 MILLION INDIVIDUAL TREE CROWNS FOR THE NATIONAL ECOLOGICAL OBSERVATORY NETWORK

Abstract: Forests provide biodiversity, ecosystem, and economic services. Information on individual trees is important for understanding forest ecosystems but obtaining individual-level data at broad scales is challenging due to the costs and logistics of data collection. While advances in remote… Read More

EVALUATION OF POSTHARVEST SENESCENCE IN BROCCOLI VIA HYPERSPECTRAL IMAGING

Abstract: Fresh fruits and vegetables are invaluable for human health, but their quality deteriorates before reaching consumers due to ongoing biochemical processes and compositional changes. The current lack of any objective indices for defining “freshness” of fruits or vegetables limits… Read More