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Marziotte, L
Dai, Z
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Authors
Nocera Santiago, G.N
Cisdeli Magalhães, P
Ciampitti, I
Marziotte, L
CARCEDO, A
Dai, Z
Topics
Artificial Intelligence (AI) in Agriculture
Type
Oral
Poster
Year
2024
2025
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1. Algorithm to Estimate Sorghum Grain Number from Panicles Using Images Collected with a Smartphone at Field-scale

An estimation of on-farm yield before harvest is important to assist farmers on deciding additional input use, time to harvest, and options for end uses of the harvestable product. However, obtaining a rapid assessment of on-farm yield can be challenging, even more for sorghum (Sorghum bicolor L.) crop due to the complexity for accounting for the grain number at field-scale. One alternative to reduce labor is to develop a rapid assessment method employing computer vision and artificial intelligence... G.N. Nocera santiago, P. Cisdeli magalhães, I. Ciampitti, L. Marziotte

2. Thermoelectric Infrared Sensor Integrated with SHA Absorber

This paper details the design of a high-performance thermoelectric infrared (IR) sensor using the UMC 0.18 μm CMOS-MEMS process, targeting the 8–14 μm wavelength for applications like IoT. To enhance performance, the sensor integrates two key innovations: a Sub-Wavelength Hole Array (SHA) absorber and a novel double-layer thermopile structure with 64 pairs of thermocouples. Finite-Difference Time-Domain (FDTD) simulations show the SHA structure achieves an average IR absorptivity of... Z. Dai