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Surveys explore AI in mental health and agriculture, clarify AI vs ML vs DL

Two recent surveys explore the application of AI and deep learning in distinct fields. One paper focuses on explainable AI for detecting mental disorders through social media, emphasizing the need for transparency in healthcare AI. Another survey reviews deep learning techniques for crops, fisheries, and livestock, highlighting challenges and future directions like multimodal data integration and edge-device deployment. Additionally, several articles discuss the distinctions between AI, Machine Learning, and Deep Learning, often with practical Python examples, while others highlight AI's role in agriculture and data science education. AI

IMPACT Clarifies distinctions between AI, ML, and DL, and surveys their applications in mental health and agriculture.

RANK_REASON The cluster contains two academic survey papers and several articles discussing the definitions and applications of AI, ML, and DL.

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 10 sources. How we write summaries →

Surveys explore AI in mental health and agriculture, clarify AI vs ML vs DL

COVERAGE [10]

  1. arXiv cs.LG TIER_1 English(EN) · Yusif Ibrahimov, Tarique Anwar, Tommy Yuan ·

    Explainable AI for Mental Disorder Detection via Social Media: A survey and outlook

    arXiv:2406.05984v2 Announce Type: replace Abstract: Mental health constitutes a complex and pervasive global challenge, affecting millions of lives and often leading to severe consequences. In this paper, we conduct a thorough survey to explore the intersection of data science, a…

  2. arXiv cs.CV TIER_1 English(EN) · Umair Nawaz, Muhammad Zaigham Zaheer, Ufaq Khan, Fahad Shahbaz Khan, Hisham Cholakkal, Salman Khan, Rao Muhammad Anwer ·

    AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock

    arXiv:2507.22101v2 Announce Type: replace Abstract: Crops, fisheries and livestock form the backbone of global food production, essential to feed the ever-growing global population. However, these sectors face considerable challenges, including climate variability, resource limit…

  3. Towards AI TIER_1 Nederlands(NL) · Hasan Ali Gültekin ·

    AI vs. ML vs. Deep Learning

    <h4>A Practical Guide With Python</h4><p><strong>AI</strong> is often treated like a single solution. In practice, it is a category label that hides <strong>three different toolboxes</strong>. If you confuse them, you usually end up building the <strong>wrong system</strong>, cho…

  4. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    2026-05-03 | 🔀 📜 The Invariants of Purpose: Crafting Digital Constitutions and Cultivating Living Roots 🔀 # AI Q: 📜 What guides you? 🤖 Multi-Agent Systems | 🏛️

    2026-05-03 | 🔀 📜 The Invariants of Purpose: Crafting Digital Constitutions and Cultivating Living Roots 🔀 # AI Q: 📜 What guides you? 🤖 Multi-Agent Systems | 🏛️ Collective Investment | 🏡 Shared Infrastructure | 🌿 Embodied Wisdom https:// bagrounds.org/convergence/2026 -05-03-the-i…

  5. Mastodon — sigmoid.social TIER_1 Deutsch(DE) · [email protected] ·

    What are the similarities, differences, and connections between AI, Machine Learning, and Deep Learning? As part of our theme year "AI - naturally with Phy

    Wo liegen die Gemeinsamkeiten, Unterschiede und Zusammenhänge von KI, Machine Learning und Deep Learning? Im Rahmen unseres Themenjahres „KI – natürlich mit Physik“ haben wir mit dem AKPIK der DPG ein Glossar für die wichtigsten Begriffe in diesem Zusammenhang erstellt, von metho…

  6. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    AI vs. ML vs. Deep Learning: A Practical Guide With Python These words are often used like they mean the same thing—but they don’t. This post explains the real

    AI vs. ML vs. Deep Learning: A Practical Guide With Python These words are often used like they mean the same thing—but they don’t. This post explains the real differences with simple Python examples, outputs, and the trade-offs that matter in real systems. :medium: https:// medi…

  7. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    National-Scale Field Delineation In Mozambique Refines Our Understanding Of Cropland Distribution, Field Size, And Deforestation Actors. -- https:// doi.org/10.

    National-Scale Field Delineation In Mozambique Refines Our Understanding Of Cropland Distribution, Field Size, And Deforestation Actors. -- https:// doi.org/10.1088/1748-9326/ae5c b4 <-- shared paper -- https:// philipperufin.github.io/blog/m ozfields-2023/ <-- shared associated …

  8. Mastodon — mastodon.social TIER_1 English(EN) · StatisticsGlobe ·

    Only 3 days left before the next series of modules in the Statistics Globe Hub begins: https:// statisticsglobe.com/hub The image below gives you a preview of s

    Only 3 days left before the next series of modules in the Statistics Globe Hub begins: https:// statisticsglobe.com/hub The image below gives you a preview of some of the graphs and topics we will explore in the coming weeks. # RStats # Python # DataScience # MachineLearning # AI…

  9. Mastodon — mastodon.social TIER_1 English(EN) · jarek_hryszko ·

    Farming in developing regions just got a smart upgrade. A new AI system tackles soil testing, crop choice, fertilizer balance, and disease detection all in one

    Farming in developing regions just got a smart upgrade. A new AI system tackles soil testing, crop choice, fertilizer balance, and disease detection all in one platform. By analyzing soil reports and environmental data, it recommends crops, calculates nutrient needs, and even sug…

  10. Mastodon — mastodon.social TIER_1 English(EN) · StatisticsGlobe ·

    A new batch of modules in the Statistics Globe Hub is about to start. You can find more information about the Statistics Globe Hub, along with the full list of

    A new batch of modules in the Statistics Globe Hub is about to start. You can find more information about the Statistics Globe Hub, along with the full list of upcoming module topics, here: https:// statisticsglobe.com/hub # rstats # Python # DataScience # MachineLearning # Stati…