The integration of photodetectors with IC circuits provides a significant
improvement over conventional designs. Featuring noise reduction, extended frequency
responses, lower power consumption, and data operations, these integrated devices open
challenging opportunities for many applications. One type of photodetector has the
potential for important applications in the life science and...
Imaging spectra of plant tissues yield considerable potential and useful information
for basic studies and agriculture practice. We constructed an imaging spectrophotometer
with spectral range from 400 nm to 1100 nm, which was used to study various
physiological events of plant germplasm: location of bundle sheath and mesophyll cells in...
Hygro-mechanical effect is a general term applied to all phenomena that involves interaction between moisture content and mechanical characteristics of hygroscopic materials by analogy to thermo-mechanical effects. The hygromechanical effects include (but are not limited to) free shrinkage/swelling, effect of moisture on elastic modulus, strength, creep, failure mechanisms, and mechano...
Shear wave velocity is a fundamental property of a granular assembly. It is a measure of the true elastic stiffness of a bulk specimen of discrete grains. Shear wave velocity is typically measured in the laboratory (e.g., using bender elements) or in-situ (e.g., using a seismic cone penetrometer, sCPT). In...
In TREC-2007, Indiana University‟s WIDIT Lab1 participated in the Blog track‟s opinion task and the polarity subtask. For the opinion task, whose goal is to "uncover the public sentiment towards a given entity/target", we focused on combining multiple sources of evidence to detect opinionated blog postings. Since detecting opinionated blogs...
In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
The abilities of plant biologists to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation and mainly to collect this data on a high-throughput scale at low cost. Deep learning-based methods have demonstrated unprecedented potential to automate...
Semantic image segmentation is a relatively difficult task in computer vision. With the advent of deep learning, semantic image segmentation is increasingly of interest for researchers because of the excellent predictions from Convolutional Neural Network (CNN). However, CNNs have proven to struggle with obtaining global context of image due to...