Refine

Claim type

Research area

Polarity

Statistics

More filters

Observationobservedoriginal resultmeasured

Claim · model-written summary

Average grading values for the three leaf colour groups were 1.0, 2.5 and 3.8.

Outcome
Average grading valuese0
Value
1.0, 2.5 and 3.8e0

Verbatim

e0

“Average grading values of the leaves of the above cited 3 groups were 1.0, 2.5 and 3.8 respectively.”

✓ located verbatim in the source · abstract, characters 1592–1692
t0

“Tobacco Leaves”

✓ located verbatim in the source · title, characters 35–49

Title

Some Leaf Characters of Flue-Cured Tobacco Leaves Sprayed with Transpiration Suppressant

Masao TANAKA Japanese Journal of Crop Science 1968. doi:10.1626/jcs.37.436

Other claims from this paper (12)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The proposed algorithm examined grain quality and grading using average extracted feature values.

Taxon
rice grainsOryza sativae0
Outcome
quality and grading of rice grainse0

Not reportedComparator

Verbatim

e0

“The quality and grading of rice grains were examined using this proposed algorithm's average values for the features that were taken out of the network”

✓ located verbatim in the source · abstract, characters 763–914

Title

A MEASURE OF QUALITY AND IDENTIFY THE BREED OF RICE GRAIN

Deepika Setti; M. Tarun Kumar; S Hemanth; et al. International Scientific Journal of Engineering and Management 2023. doi:10.55041/isjem00254

Other claims from this paper (1)
Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The TBC-YOLOv7 model reaches average precision values of up to 90% for one bud with one leaf.

Taxon
teat0
Organ / stage
one bud with one leafe2
Outcome
average precision valuese2
Value
90%e2

Verbatim

t0

“tea bud grading detection”

✓ located verbatim in the source · title, characters 49–74
e2

“with average precision values of up to 90% for one bud with one leaf”

✓ located verbatim in the source · abstract, characters 1445–1513

Title

TBC-YOLOv7: a refined YOLOv7-based algorithm for tea bud grading detection

Siyang Wang; Dasheng Wu; Xinyu Zheng Frontiers in Plant Science 2023. doi:10.3389/fpls.2023.1223410

Other claims from this paper (7)
Method / resourceauthor interpretationoriginal resultmeasured

Claim · model-written summary

An image processing system classified grains into Good, Average, and Bad classes

Outcome
classify the grains into Good, Average and Bad classe0

Not reportedComparatorValue

Verbatim

t0

“Wheat Grains”

✓ located verbatim in the source · title, characters 38–50
e0

“This project illustrates the automatic grading system which process the grain image digitally and classify the grains into Good, Average and Bad class by taking predefined values into consideration with the help of Digital Image Processing and the grains, weed particles, stones and other foreign materials are easily distinguished.”

✓ located verbatim in the source · abstract, characters 758–1090

Title

Quality Identification and Grading of Wheat Grains using Image Processing Techniques

Vinay K Kolur; Swati Padagatti 2021 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT) 2021. doi:10.1109/iceeccot52851.2021.9708017

Other claims from this paper (1)
Method / resourceauthor interpretationoriginal resultmeasured

Claim · model-written summary

The image processing system distinguished grains, weed particles, stones, and other foreign materials

Outcome
grains, weed particles, stones and other foreign materials are easily distinguishede0

Not reportedComparatorValue

Verbatim

t0

“Wheat Grains”

✓ located verbatim in the source · title, characters 38–50
e0

“This project illustrates the automatic grading system which process the grain image digitally and classify the grains into Good, Average and Bad class by taking predefined values into consideration with the help of Digital Image Processing and the grains, weed particles, stones and other foreign materials are easily distinguished.”

✓ located verbatim in the source · abstract, characters 758–1090

Title

Quality Identification and Grading of Wheat Grains using Image Processing Techniques

Vinay K Kolur; Swati Padagatti 2021 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT) 2021. doi:10.1109/iceeccot52851.2021.9708017

Other claims from this paper (1)

Lexical search (BM25). All words must match; if nothing does, any word. Organism names also match every spelling of the same organism. No semantic search yet.